// If version is a deleted marker, set this header as well
		if objInfo.DeleteMarker && del { // only returned during delete object
			w.Header()[xhttp.AmzDeleteMarker] = []string{strconv.FormatBool(objInfo.DeleteMarker)}
		}
	}

	if objInfo.Bucket != "" && objInfo.Name != "" {
		if lc, err := globalLifecycleSys.Get(objInfo.Bucket); err == nil && !del {
			lc.SetPredictionHeaders(w, objInfo.ToLifecycleOpts())
		}
	}

Se você precisar aplicá-lo, use `OAuth2PasswordRequestFormStrict` em vez de `OAuth2PasswordRequestForm`.

///

* Um `client_id` opcional (não precisamos dele em nosso exemplo).
* Um `client_secret` opcional (não precisamos dele em nosso exemplo).

/// info | Informação

O `OAuth2PasswordRequestForm` não é uma classe especial para **FastAPI** como é `OAuth2PasswordBearer`.

    url: https://github.com/fastapi/fastapi/discussions/categories/questions
  - name: Show and tell
    about: Show what you built with FastAPI or to be used with FastAPI.
    url: https://github.com/fastapi/fastapi/discussions/categories/show-and-tell
  - name: Translations
    about: Coordinate translations in GitHub Discussions.

      description: If compiling from source
  - type: textarea
    id: what-happened
    attributes:
      label: Current behavior?
      description: Also tell us, what did you expect to happen?
      placeholder: Tell us what you see!
    validations:
      required: true
  - type: textarea
    id: code-to-reproduce
    attributes:
      label: Standalone code to reproduce the issue

In many frameworks and systems just handling security and authentication takes a big amount of effort and code (in many cases it can be 50% or more of all the code written).

**FastAPI** provides several tools to help you deal with **Security** easily, rapidly, in a standard way, without having to study and learn all the security specifications.

But first, let's check some small concepts.

## In a hurry? { #in-a-hurry }

Ese "esperar otra cosa" normalmente se refiere a las operaciones de <abbr title="Input and Output">I/O</abbr> que son relativamente "lentas" (comparadas con la velocidad del procesador y la memoria RAM), como esperar:

* que los datos del cliente se envíen a través de la red
* que los datos enviados por tu programa sean recibidos por el cliente a través de la red

 
<!--- Provide a general summary of the issue in the Title above -->

## Expected Behavior
<!--- If you're describing a bug, tell us what should happen -->
<!--- If you're suggesting a change/improvement, tell us how it should work -->

## Current Behavior
<!--- If describing a bug, tell us what happens instead of the expected behavior -->
<!--- If suggesting a change/improvement, explain the difference from current behavior -->

# Note that numpy 2.1.0 does not support python 3.9
numpy >= 2.0.0, < 2.2.0
wheel ~= 0.41.2
h5py >= 3.11.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras

* 100% test coverage: cobertura de tests del 100%
* back and forth: de un lado a otro
* I/O (as in "input and output"): I/O (do not translate to "E/S")
* Machine Learning: Machine Learning (do not translate to "Aprendizaje Automático")
* Deep Learning: Deep Learning (do not translate to "Aprendizaje Profundo")
* callback hell: callback hell (do not translate to "infierno de callbacks")

    compiling from source placeholder: validations: required: false

-   type: textarea id: what-happened attributes: label: Current Behaviour?
    description: Also tell us, what did you expect to happen? placeholder: Tell
    us what you see! value: "A bug happened!" render: shell validations:
    required: true

-   type: textarea id: code-to-reproduce attributes: label: Standalone code to